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Parsing live data(text) from "https://www.worldometers.info/coronavirus/" and viewing the updates in table format for each country and can be searched by country name then converting to csv format using pandas for analysis
Aasess/CoronaTracker
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Step1 : Development(CoronaProject + Demo for project dir) We need to parse the data(text) from "https://www.worldometers.info/coronavirus/". For this I am using BeautifulSoup library + Requests library. Requests allows us to make HTTP request to get infomation from website and after that we can parse the http result using BeautifulSoup.(Can also use Pandas using read.html_csv() but this site doesn't allow to read table using Pandas.i.e Authentication error also BeautifulSoup is really powerful for parsing compared to pandas). requirement: 1:Install beautifulSoup along with lxml(which is parser.Can use any parser. It doesn't matter) 2: Install requests 3:Install django 4:Create django project and apps and templates or you can download the file 5: Run the server note: "watch the project demo " note: "bootstrap is used for creating the templates" Step2:Web Scraping: Storing above parsed data to csv file(coronacsv:masterbranch) 2.1: first Convert the data parsed using beautifulSoup to csv format.(Those who want to use can use the dataset).For this I will be using Pandas. I will be working on TimeSeries Analysis considering different project. Those who want to work on the same Development can do the following * In App -> views.py after line53 of coronatracker..... copy the modified code of"Parsingandtocsv.py file from coronacsv directory" Step3: TimeSeriesAnalysis Description in Analysis folder
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Parsing live data(text) from "https://www.worldometers.info/coronavirus/" and viewing the updates in table format for each country and can be searched by country name then converting to csv format using pandas for analysis
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